Bibliographic record
Abstract
In 1890, the interior of the Québec-Labrador peninsula was still virtually unexplored. Ten years later, the blank on the map had been filled : geology, physio-graphy, climate, vegetation, fauna and inhabitants of the region were known, at least in their great lines, thanks to the remarkable amount of exploratory work done by the Canadian geologist A. P. Low. In thirteen seasons, Low sailed, canoed, dog-sledded and snowshoed some 10,000 miles in and around the peninsula. He gave the first accurate picture of the country, traced the outline of the Labrador Trough and gave the first description of the iron ores it contains. He surveyed the course of the principal rivers and a large portion of the northern and western coasts. His huge 1895 report is still considered the best work ever to have been printed about the region. Outside Québec-Labrador, Low worked in Gaspé, Manitoba, and was leader of the 1903-04 Canadian Arctic expedition on board the Neptune; on that occasion, he took formal possession of the Arctic Archipelago on behalf of Canada. Today's scientist, greatly helped by the airplane and modem technique, should be forever grateful to this indefatigable predecessor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".